Nov 2018
Seminer Announcement: "Machine Learning for Medicine: what can we learn from medical data?" by Dr. İslem Rekik

"Machine Learning for Medicine: What can we learn from medical data?"
Speaker : Dr. İslem Rekik
Date : November 30th, 2018 (Friday)
Time : 14:00
Location : Conference Hall, ARI-9 Building 

It is becoming increasingly clear that machine learning (ML) will transform many aspects of healthcare delivery, including patient diagnosis and treatment. In the coming years, hospitals will be equipped with smart artificial intelligence (AI) diagnostic toolkits that aid doctors make a more accurate and efficient diagnosis of the patient at hand. This seminar will present different machine learning methods developed for improving medical care, including abnormal tissue segmentation tasks, classification and predictive modeling. For more information about our ML projects for medicine, please check BASIRA lab website and YouTube channel. With the medical imaging industry at the start of a new wave of AI-fuelled technology innovation, now it is the time to develop smarter, robust and effective ML methods to meet learning from medical data challenges.

Short Bio
islem-rekikDr. İslem Rekik is an assistant professor in Faculty of Computer and Informatics Engineering at İstanbul Technical University.  Previously, Dr. Rekik was an assistant professor (lecturer) within Computing at the University of Dundee. Also, she was a postdoctoral research assistant at the University of North Carolina (IDEA lab) following a PhD in "Neuroimaging and Computer Sciences" from the University of Edinburgh in 2014. She is the director of BASIRA lab at the University of Dundee and a member of the Computer Vision and Image Processing (CVIP) research group. BASIRA (Brain And SIgnal Research & Analysis) aims to infuse advanced computer vision and machine-learning methods into big neuroimaging and signal data analysis for improving healthcare and wellbeing. Specifically, we develop advanced medical data analysis techniques for better understanding brain development and ageing in health and disease.